In a production scanning environment, the digital output of a scanned paper document is often represented and stored in binary (Black and White) form because of greater efficiency in storage and transmission, particularly for textual images. The capture of a binary image requires an image thresholding process installed in a scanner, which converts digital gray scale signals captured by a CCD sensor (usually, 8 bits per pixel) into binary signals (1 bit per pixel). Since an image thresholding is an image data reduction process, it often results in unwanted image artifacts or image information loss, such as speckle noises in the document background or loss of low contrast characters. In the prior art, there are numerous adaptive thresholding techniques for producing an optimal quality binary image. However, an adaptive thresholding technique has yet to be found that automatically produces a clean, readable binary image for every captured gray scale image in a batch of paper documents due to variations of paper background and content. As a result, the production document scanning often requires intensive labor in the form of visual image quality inspection warranting that every captured binary image is readable.
Clearly, there is a need for an improved scanning system and process that is capable of producing a clean, readable binary image of text or the like without the need for a visual image quality inspection. Ideally, such a system and process would be sufficiently compatible with presently available scanning components to allow the use of the system on scanners presently in use, and to minimize the need for the design and manufacture of new components.